Based on the Lasso algorithm and a bidirectional
fixed multiple linear regression model, this study comprehensively investigates
the impact of macro and micro factors on the credit spread of ESG bonds in
China. Research has shown that the credit spread of ESG bonds is negatively
correlated with macro factors such as regional per capita GDP, local fiscal
revenue, money supply, stock market returns, as well as micro factors such as
total issuance amount, entity rating, debt rating, guaranteed delivery,
state-owned equity certification, and green certification. Meanwhile, the
credit spread is positively correlated with factors such as RMB exchange rate,
fuel oil price, and urban investment bond certification. Further heterogeneity
analysis indicates that ESG bonds are more significantly impacted by external
factors after the epidemic, and the safety of state-owned bonds is further
highlighted. The default rate of ESG urban investment bonds in the southwest
region is relatively high, and the key to reducing their credit spread is to
obtain green certification for establishing a positive market image. The above
research conclusions provide important references for optimizing the bond
pricing mechanism and reasonably evaluating the risks of ESG concept financing
projects.
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